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20192026
most citedThe Effect of Wearing a Mask on Face Recognition Performance: an Exploratory Study

33 citations · 195 across the 88 of their papers we have counts for

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Showing 2022 · cs.CVShow all

16 papers · 2 filters

cs.CV2022★ 3 cited

Periocular Biometrics: A Modality for Unconstrained Scenarios

Fernando Alonso-Fernandez, Josef Bigun, Julian Fierrez +3

Periocular refers to the externally visible region of the face that surrounds the eye socket. This feature-rich area can provide accurate identification in unconstrained or uncoope…

cs.CV2022

Unsupervised Face Recognition using Unlabeled Synthetic Data

Fadi Boutros, Marcel Klemt, Meiling Fang +2

Over the past years, the main research innovations in face recognition focused on training deep neural networks on large-scale identity-labeled datasets using variations of multi-c…

cs.CV2022

A Survey on Computer Vision based Human Analysis in the COVID-19 Era

Fevziye Irem Eyiokur, Alperen Kantarcı, Mustafa Ekrem Erakın +8

The emergence of COVID-19 has had a global and profound impact, not only on society as a whole, but also on the lives of individuals. Various prevention measures were introduced ar…

cs.CV2022★ 7 cited

Stating Comparison Score Uncertainty and Verification Decision Confidence Towards Transparent Face Recognition

Marco Huber, Philipp Terhörst, Florian Kirchbuchner +2

Face Recognition (FR) is increasingly used in critical verification decisions and thus, there is a need for assessing the trustworthiness of such decisions. The confidence of a dec…

cs.CV2022★ 1 cited

Fairness in Face Presentation Attack Detection

Meiling Fang, Wufei Yang, Arjan Kuijper +2

Face recognition (FR) algorithms have been proven to exhibit discriminatory behaviors against certain demographic and non-demographic groups, raising ethical and legal concerns reg…

cs.CV2022

Towards Explaining Demographic Bias through the Eyes of Face Recognition Models

Biying Fu, Naser Damer

Biases inherent in both data and algorithms make the fairness of widespread machine learning (ML)-based decision-making systems less than optimal. To improve the trustfulness of su…